add_pcs: Add PCA Loadings

In romic: R for High-Dimensional Omic Data

Add PCA Loadings

Description

Add Principal Components Analysis Loadings to a tidy or triple omics dataset.

Usage

add_pcs(
  tomic,
  value_var = NULL,
  center_rows = TRUE,
  npcs = NULL,
  missing_val_method = "drop_samples",
  label_percent_varex = TRUE,
  verbose = TRUE
)

Arguments

tomic	Either a tidy_omic or triple_omic object
value_var	An abundance value to use with hclust
center_rows	center rows before performing PCA
npcs	number of principal component loadings to add to samples (default is number of samples)
missing_val_method	Approach to remove missing values: drop_features Drop features with missing values drop_samples Drop samples which are missing all features, then drop features impute Impute missing values
label_percent_varex	If true then PCs will be labelled by the percent of variability they explain.
verbose	extra reporting messages

Value

A tomic object with principal components added to samples.

Examples

add_pcs(brauer_2008_triple, npcs = 5)

romic documentation built on Sept. 21, 2023, 9:06 a.m.